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Which Model of Technology Transfer for
Nanotechnology? A Comparison with Biotech and Microelectronics
Corine Genet, Khalid Errabi, Caroline Gauthier
To cite this version:
Corine Genet, Khalid Errabi, Caroline Gauthier. Which Model of Technology Transfer for Nanotech- nology? A Comparison with Biotech and Microelectronics. Technovation, Elsevier, 2012, 32 (3-4), p.
205-215. �10.1016/j.technovation.2011.10.007�. �hal-00749152�
1
WHICH MODEL OF TECHNOLOGY TRANSFER FOR NANOTECHNOLOGY?
A Comparison with Biotech and Microelectronics
Corine Genet, Khalid Errabi, Caroline Gauthier Grenoble Ecole de Management (GEM) 12 rue Pierre Sémard, 38000 Grenoble, France
Phone: + 33 4 76706297
Contact e-mail: corine.genet @grenoble-em.com Website: www.nanoeconomics.eu
Abstract.
Nanotechnologies are often presented as breakthrough innovations, where technology transfer and knowledge-bridging will play a pivotal role in the industrial dynamics. This article investigates the model of knowledge transfer in the nanotechnologies in depth, by comparing it with the models of two recently emerged technologies: biotech and microelectronics. Our results show that the nanotechnology transfer model is very different from that involved in biotechnology evolution: while small-medium firms play a valuable technology-bringing role, the central function of “translating” new knowledge between public research and industry in carried by the larger firms, just as it was in the early stages of the microelectronics sector.
Keywords.
Nanotechnology – biotechnology – microelectronics – technology transfer
Acknowledgements: we acknowledge the financial support of ANR (ANR-07-NANO-026-
01). The authors would like to thank the participants of COMS2010 Alburquerque, USA and
the participants of the MCOI seminar (www.grenoble-innovation.eu) at Grenoble Ecole de
Management. We are grateful to Jon Morgan for his paper editing. Usual caveats apply.
2
WHICH MODEL OF TECHNOLOGY TRANSFER FOR NANOTECHNOLOGY?
A Comparison with Biotech and Microelectronics
Abstract.
Nanotechnologies are often presented as breakthrough innovations, where technology transfer and knowledge-bridging will play a pivotal role in the industrial dynamics. This article investigates the model of knowledge transfer in the nanotechnologies in depth, by comparing it with the models of two recently emerged technologies: biotech and microelectronics. Our results show that the nanotechnology transfer model is very different from that involved in biotechnology evolution: while small-medium firms play a valuable technology-bringing role, the central function of “translating” new knowledge between public research and industry in carried by the larger firms, just as it was in the early stages of the microelectronics sector.
Keywords.
Nanotechnology – biotechnology – microelectronics – technology transfer
Introduction
It seems likely that the nanotechnology will be a significant factor in the 21
stcentury. The
U.S. National Nanotechnology Initiative (NNI) has defined nanotechnology as “encompassing
the science, engineering, and technology related to the understanding and control of matter at
the length scale of approximately one to 100 nanometers”. Nanotechnologies include the
research and development of materials, devices, and systems that have novel properties and
functions due to their nanoscale structures or components (Chen and Roco 2009).They offer
the potential for ground-breaking scientific research, and hold out the promise both of
increasing efficiency in traditional industries, and of fostering radically new applications in
emerging technologies. Nanotechnologies are expected to have a huge positive impact on
economic growth and to create new markets, which is why most industrialized countries and
3 companies have invested billions of dollars in nanotech developments, and are expecting great returns.
Nanotechnologies are technologically multidisciplinary as well as have cross-industrial utility (Linton and Walsh 2004): product and process applications have been and are being developed in areas ranging from medicine, electronics, optics, telecommunications, aerospace to energy (Niosi 2007). Nanotechnology is seen as a breakthrough innovation, with technology transfer and knowledge-bridging playing a pivotal role in its birth and growth (Rothaermel and Thursby 2007). This article investigates the model of technology transfer in the nanotech sector in depth in order to guide decision-makers in making the right choices for its further developments. To do so, we compare the case of the evolution of nanotech with those of two other recently emerged technologies - biotechnology and microelectronics: each of which has held out the innovative prospect of producing existing products using a completely different set of technical competencies (Walsh and Kirchhoff 2002). Linton and Walsh (2004) describe them as „materials based technologies with concurrent product and process innovation curves and regard them as the likely engines of future economic growth‟.
Nanotechnologies are often compared to biotechnologies, due to the breakthroughs the latter have generated in the pharmaceutical industry (Zucker et al., 2007). The integration of nanotechnologies could threaten the leadership of established firms in the same way, rendering their accumulated expertise redundant (Hill et al., 2003), and creating emerging opportunities for new firms (Shea, 2005). Such new entrants are better placed to take advantage of disruptive technologies than are incumbents, who may suffer from organizational inertia and short-term incentives, and face the prospect of having to cannibalize their own markets. If the comparison (with biotechnologies) holds, small-medium firms (SMEs) are likely to play a key role in the industrial dynamics of nanotechnologies, leading to industrial architectures mainly composed of dedicated spin-offs focused on bringing nanotechnology processes, tools and first generation materials, devices and systems to market (Chachamidou and al. 2008).
But nanotechnologies can also be compared to microelectronics, although here the
comparison seems to point to a different industrial landscape. As Abernathy and Utterback
(1978) have highlighted, large firms such as Fairchild Semiconductors, IBM and Texas
Instruments played the fundamental roles in this field‟s first development phases in the 60s
and 70s. The development of nanotechnologies requires the same kind of large knowledge
4 base that incumbent firms possess, implying that large firms will predominate in both the exploration and commercialization of nanotechnology potentials, and that small-medium firms will play lesser roles.
This paper focuses on the place of small-medium firms in the knowledge transfer model of this new technology, addressing the questions of: What role do SMEs play in the co- production and translation of knowledge? Is it central, as it is in the biotech sector? Are they one of several avenues via which knowledge and technology is transferred from academe to industry? Or do they play a role similar to how SMEs operate in the microelectronic sector, as suppliers of specific equipment to large companies? To explore the model of technology transfer in nanotechnology, we have built a database of the (approx) 10,000 firms that patented in nanotechnologies between 1990 and 2008, using a validated search strategy based on keywords (Mogoutov et al., 2007) to extract patents from PatStat. The database was cross- referenced against ORBIS to retrieve firms‟ financial data, as well as to identify and then extract small-medium firms
The paper is structured as follows. Firstly, we question the model of knowledge transfer in nanotechnology by considering the technological evolutionary patterns of the biotechnology and microelectronics industries. We then describe our empirical data and methods of analysis, and lastly present and discuss our results.
Are the knowledge transfer models of nanotechnology, biotechnology and microelectronics similar?
Comparing nanotechnology with biotechnology
Many scholars (Rothaermel and Thursby 2007; Zucker and Darby 2007; Niosi 2007; Youties
et al. 2008) have found that nanotechnology and biotechnology have exhibited similar
technological evolutionary patterns. The pattern of biotechnology development has largely
been based on the creation of research-intensive SMEs (Orsenigo, 1989, 2001; Gambardella,
1995; Sharp 1985, Kenney, 1986), usually university spin-offs formed through the
collaboration of a scientist and a professional manager, backed by venture capital, with the
aim of applying new scientific discoveries to commercial product development (Mangematin
et al. 2003). In many cases these spin-offs benefited from access to top world experts (usually
university scientists) on specific topics, and the firms‟ expertise has essentially been in
5 research areas directly related to the scientific field of their expert‟s original laboratory. The product of such firms has exclusively almost been research within a relatively narrow range, and – in terms of their ability to translate their research into innovations - these small-medium firms have typically lacked critical assets in manufacturing, testing and marketing areas, access to regulatory agencies and to distribution channels in the pharmaceutical and food industries. In order to integrate such biotechnology innovation capabilities, SMEs have had to develop different forms of collaboration with established firms. It has been argued that since large pharmaceutical companies were committed to the old organic chemistry paradigm, where all their competences were concentrated, they could not easily internalize the new biotechnological knowledge; and that few of them had the absorptive capacity required to internalize the new paradigm or could construct such a capacity rapidly (Pyka and Saviotti, 2005). So these collaborative arrangements between small and large firms provided both partners with access to the competences and assets they lacked: large companies to the SMEs‟
scientific discoveries - and the potential of receiving royalties if they had commercial potential - and SMEs to commercial markets. Consequently, the biotechnology industry is characterized by a network structure of inter-organizational alliances among the different actors involved: research institutions and large and small-medium firms, in which the latter are seen as a nexus, mediating between the scientists and the large established commercial players (Mangematin et al. 2003).
In such frameworks, the SMEs play a key role in the process of co-producing and translating knowledge, acting essentially as intermediaries bridging the gap between public research institutions and large chemical and pharmaceutical companies, buying research outputs from their discoverers, developing or refining them towards specific objectives, and then selling this knowledge on to larger partners for downstream commercialization (Greis et al., 1995;
Zucker and Darby, 1997). Orsenigo (1989) argues that this specialization of biotech start-ups
“… provided an institutional solution to the transfer problem” and Orsenigo et al. (2001) refer to these new organizations as “specialized technology originators”, while Pyka and Saviotti (2005) refer to their role as “translators”. The biotech technology transfer model thus has SMEs as central economic actors.
Zucker and Darby (2007) show that the evolution of nanotechnology is following the same pattern: firms are entering where and when academics scientists publish breakthrough articles.
They suggest that the production of nanotechnological knowledge is embedded in the wider
social context of cross-institutional collaboration, and expect development patterns to be
6 based on strong ties between academe and industry leading to the creation of spin-offs. In their framework, the process of knowledge transfer from science and engineering to industrial application involves academic (Zucker and Darby 2007). Top scientists‟ involvement contributed importantly to the appropriability of biotechnology inventions, and a similar process appears to have started in nanotechnology (Zucker and Darby 2007). In such high- technology sectors as biotechnology or nanotechnology, newly founded firms have been perceived as the main drivers of technological change, and we could this argue that this type of actor is likely to be in a better position than larger firms to exploit the new opportunities created by the emergence of nanotechnologies. To examine whether the technological transfer model of nanotechnology mirrors that of the biotechnology industry in terms of the role of SMEs, we test:
Proposition # 1: Do SMEs play a key role in co-producing and transferring knowledge in nanotechnology by acting as a node of high centrality between public research and large firms in nanotech co-patenting networks.
Comparing nanotechnology with microelectronics
Abernathy and Utterback (1978), Peck (1986) and Braun and MacDonald (1978) have
stressed the fundamental role that large firms played in the early stages of the
microelectronics industry. Peck (1986) and Levin (1982) point out that there was no profound
interaction between scientific theory and technological practice during the first years of the
development of the transistor: the integrated circuit concept did not rest on any novel
application of scientific theory: rather it was an engineering achievement. In the same vein,
Mowery (1983) argues that the evolution of the industry structure is best explained by
reference to the central role of manufacturing processes: “the pure science input into
semiconductor innovation currently is rather modest; it is production engineering that is
critical.” Arcangeli et al. (1991) highlighted that the accumulation of knowledge in the early
stage of microelectronics industry was mainly based on the history, technical knowledge and
forms of corporate organization inherited from electromechanical technologies. Braun and
MacDonald (1978) explained that, in the first two decades of the computer and semiconductor
industries, large integrated producers (such as AT&T and IBM) designed their own solid-state
components, manufactured the majority of the capital equipment used in their production
process and utilized internally produced components in the manufacture of electronic
computers and computer software that was leased or sold to their customers.
7 However Levin (1982) points out that, by the late 1970s, technical progress increasingly required more research than had characterized industry‟s early stage, while Peck (1986) notes that three entities were already positioned with large programs to carry out such research:
IBM, AT&T and the large Japanese computer and semiconductor firms, and that large-scale R&D projects carried out jointly by profit-making corporations became increasingly important in the computer and semiconductor industries. These efforts - largely organized and funded by governments - generally focused on longer term generic research, leaving product and process development to smaller individual companies, thus making up for the small scale their research capabilities. In that framework, a few large firms played the fundamental roles in the process of knowledge co-production, based on partnerships created in the early stage of the microelectronics industry. Thus internal R&D and large-scale research projects which involved both large companies and public research seems to have been the principal vector of the co-production and transfer of knowledge, positioning the large firms as the central economic actors. A recent paper by Mangematin et al. (2010) argues that, in nanotechnology development, large firms hybridize their existing knowledge base with these newly emerging technologies, and shows how they are investing in pre-adaptation so as to speed up the development of new technologies and to be ready as markets emerge. This pattern suggests that the nanotech technology transfer model is closer to that of microelectronics, with large firms having the fundamental role, and contention which we examine in this paper by testing a second proposition:
Proposition # 2: Do large firms play a fundamental role in co-producing and transferring knowledge in nanotechnology by acting as a node of high centrality directly linking the industry’s co-patenting network with public research in nanotechnology.
Data and Methodology
Data acquisition
To explore these two propositions, we built a database of firms involved in nanotechnologies, to develop a data set of nanotechnology-related patents from 1998-2006, which were collected from the PATSTAT EPO database (which collects data coming from 73 offices worldwide).
We identified 617,000 nanotechnology applications from the more than 65,000,000 patents
listed PATSTAT in our focal period, and used a keyword-based approach to select a subset of
8 the patents related to nanotechnologies (Mogoutov et al. 2007). We ended up with 9,447 companies that had patented in nanotechnologies.
We matched this database with ORBIS to discover economic and financial information about our data set firms. ORBIS is a comprehensive world-wide database of information on 60 million companies, combining information from nearly 100 sources filtered into various standard report formats. This search found 3,719 firms involved in nanotechnology (which we label “nanotech firms”). ORBIS define four categories of firms: (VL) Very Large companies (operating revenue of at least US$40m or over 1000 employees), (L) Large companies (operating revenue at least US$14m or over 150 employees), (M) Medium sized companies (operating revenue at least US$ 1.4 million or over 15 employees and (S) Small companies (those not included in another category). Using this classification, we identified 2,140 (58%) of our nanotech firms as being large or very large firms, and 1,579 (42%) as being small or medium firms (SMEs).
Tables 1, 2, 3 and 4 describe the main characteristics of our population of 3,719 nanotech firms.
1We observe that 71% of nanotech SMEs were created after 1990. Since the potential of understanding the nanoscale properties of matter and the formulation of key research opportunities were becoming clearer by 2000 (Roco, Williams and Alivisatos, 2000) - we can suppose that these firms were created to apply these new scientific discoveries to commercial product development. In contrast, 70% of large-very nanotech large firms were created before 1990: we can characterize these firms as investing in nanotechnology, but being not dedicated nanotech companies.
1 The data preparation and the statistical analysis for this paper were generated using SAS software. Copyright, SAS Institute Inc.
9
Table 1 Firm's Size by Year of IncorporationFrequency Percent Row Pct Col Pct
Firm's Size -2 Levels- (ORBIS)
Year of Incorporation
pre-1950 1951-1980 1981-1990 post 1990 Total
SM Firms 43
1.16 2.72 6.23
147 3.95 9.31 23.11
265 7.13 16.78 42.47
1,124 30.22 71.18 63.54
1,579 42.46
LVL Firms 647
17.40 30.23 93.77
489 13.15 22.85 76.89
359 9.65 16.78 57.53
645 17.34 30.14 36.46
2,140 57.54 Total
%age
690 18.55
636 17.10
624 16.78
1,769 47.57
3,719 100.00
Table 2 shows that about 90% of nanotech SMEs are located in Europe and US/Canada (while large-very large nanotech firms are mostly located in Europe (48%) and US Canada (24%) but also in Asia (21%). Mangematin et al. (2010) have shown that the investment of Asian firms in nanotechnology is mainly centered on nanoelectronics, a sector that remains dominated by large companies.
Table 2 Firm Size by Geographical Area
Frequency Percent Row Pct Col Pct
Firm's Size -2 Levels- (ORBIS)
Geographical Area
ASIA EU27 OTHERS US/Canada Total
SM Firms 60
1.61 3.80 11.95
669 17.99 42.37 39.35
101 2.72 6.40 39.92
749 20.14 47.44 59.26
1,579 42.46
LVL Firms 442
11.88 20.65 88.05
1031 27.72 48.18 60.65
152 4.09 7.10 60.08
515 13.85 24.07 40.74
2,140 57.54 Total
%age
502 13.50
1,700 45.71
253 6.80
1,264 33.99
3719 100.00
Table 3 shows that 42% of nanotech SMEs have high nano patenting intensity (more than
50%), but 60% of the large nanotech firms have nano patenting intensities of less than 10%.
10
Table 3 Firm's Size by Nano Patenting IntensityFrequency Percent Row Pct Col Pct
Firm's Size -2 Levels- (ORBIS)
Company's Nano Patenting Intensity LOW
(<10%)
MEDIUM (10-<50%)
HIGH (50-<100%)
ULTIMATE (100%)
Total
SM Firms 293
7.88 18.56 18.58
621 16.70 39.33 51.45
368 9.90 23.31 70.23
297 7.99 18.81 72.26
1,579 42.46
LVL Firms 1,284
34.53 60.00 81.42
586 15.76 27.38 48.55
156 4.19 7.29 29.77
114 3.07 5.33 27.74
2,140 57.54 Total
%age
1,577 42.40
1,207 32.45
524 14.09
411 11.05
3,719 100.00
Table 4 lists the main industrial sectors where our 3,719 nanotech firms operate, based on the North American Industry Classification System (NAICS), and shows that nanotech SMEs are mainly involved in the Professional, Scientific and Technical Services sector (20%), while large-very large nanotech firms are mainly found in the Pharmaceutical and Medicine Manufacturing, the Control Instrument and the Semiconductor and Other Electronic Component Manufacturing sectors.
Table 4 Firm's Size by industry
Frequency Percent Row Pct Col Pct
NAICS 2007 Firm's Size -2 Levels-(ORBIS)
LVL Firms SM Firms Total Scientific Research and Development Services 93
2.50 22.96 4.35
312 8.39 77.04 19.76
405 10.89
Pharmaceutical and Medicine Manufacturing 203 5.46 81.53 9.49
46 1.24 18.47 2.91
249 6.70
Navigational, Measuring, Electromedical and Control
Instruments Manufacturing 129
3.47 59.17 6.03
89 2.39 40.83 5.64
218 5.86
Semiconductor and Other Electronic Component 134 68 202
11
Manufacturing 3.60
66.34 6.26
1.83 33.66 4.31
5.43
Total
%age
2,140 57.54
1,579 42.46
3719 100.00
According to the NAICS, the Professional, Scientific and Technical Services sector is specialized, and provides services to clients in a variety of industries and (in some cases) to households. Activities performed include (and involve expertise in): legal advice and representation; accounting, bookkeeping and payroll services; architectural, engineering and specialized design services; computer services; consulting services; research services;
advertising services; photographic services; translation and interpretation services; veterinary services etc.. It can be argued that these activities represent valuable ways in which nano technologies can be exploited in client companies‟ innovation processes and, therefore, it is reasonable to expect that nanotech SMEs play a critical knowledge-bridging role in such situations.
Network construction
The network concept is a relatively new methodology that is used in many disciplines - including economics, sociology and organizational theory - to analyze different interaction structures among actors. Developed within the framework of graph theory, it is increasingly used to study industry networks composed of different but interrelated groups of actors (e.g., firms, suppliers, customers, universities, and other institutions). To capture the role of SMEs in the process of nanotech knowledge co-production, we introduce network concepts and measures to represent the relations between such different actors as universities, nonprofit institutions, governmental institutions, hospitals and companies, focusing on technological collaboration expressed through co-patenting. Niosi (2007) reminds us that patents are key to protecting intellectual propriety in both the biotechnology and nanotechnology arenas and, despite the objection that patents are by definition static and may thus represent incomplete criteria with which to measure knowledge flows, we argue that co-patent networks offer a valuable way of examining R&D collaboration structures (Goetze C., 2010) because they mirror the results of collaborations between actors.
We use two different analytical units in this research. We first analyze institutions‟ co-
patenting networks in a way that represents each category of actor involved: universities,
12 nonprofit institutions, governmental institutions, hospitals and firms, which are represented according to size (small-medium or large-very large). Second, we analyze co-patenting networks at the firm level. In both network models, nodes represent the analytical units - categories of institution (universities, nonprofit institutions, governmental institutions, hospitals and firms) in the first network and firms in the second – and links represent the co- patent relations between different actors. Visualizing core networks allows us to identify the salient collaborations between actors and thus infer the role of firms in the nanotechnology knowledge transfer model. We adopted Cytoscape Collaboration‟s open-source network visualization and analysis software in developing our framework.
2Network analysis
First, we undertook a topological analysis of the two types of co-patenting networks, a technique that characterizes them via various statistical measures (Albert and Barabasi, 2002):
- Network size: shows the coverage of the field and reports the number of nodes and number of links;
- Component size: A component is an isolated sub-network in a disconnected network, and thus represents a independent group in the field;
- Density: is understood as the number of all realized links divided by the number of all possible ones (Wasserman and Faust, 1994);
- Network diameter: indicates the distance between the two most distant nodes (i.e. the longest „shortest path‟ between any node couple on the graph);
- Average path length (or Average Distance) is the average length of the shortest node- couple paths (calculated by summing all the shortest paths and then dividing by the total number of node couples);
- Degree: is the simplest topological index, corresponding to the number of nodes adjacent (i.e., directly connected) to a given node (also called its "first neighbors") ; - Average degree: is the average number of links a node has with other nodes;
- Average Clustering coefficient: is the average of all the nodes‟ clustering coefficients.
A single node‟s clustering coefficient is the ratio of the number of links between the node‟s neighbors (the nodes directly connected to it) to the number of possible links between them. The co-patent network‟s average coefficient thus indicates the tendency
2 Cytoscape is a collaborative project between the Institute for Systems Biology (Leroy Hood lab), the University of California San Diego (Trey Ideker lab), Memorial Sloan-Kettering Cancer Center (Chris Sander lab), the Institut Pasteur (Benno Schwikowski lab), Agilent Technologies (Annette Adler lab) and the University of California, San Francisco (Bruce Conklin lab). (http://www.cytoscape.org).
13 for analytical units to form „local‟ clusters, with denser local clusters indicating nodes that are more likely to be influenced by their neighbors.
Secondly, since we are focusing on centrality, which concerns the roles of individuals (in our case, firms) in a network, we measure several related factors (such as degree, closeness, betweenness and eccentricity).
- Degree: is the number of direct links a particular node has;
- Eccentricity: of a node is calculated by computing the shortest path between it and all other nodes on the graph;
- Closeness: The closeness of a node is calculated by computing the shortest paths between it all the other nodes in the graph and summing these values. Closeness should be always compared to eccentricity: a node with high eccentricity + high closeness is very likely to be central on the graph (and thus to the network);
- Betweenness: provides an elaborated and informative centrality index, and counts the number of shortest paths linking a node couple (v1, v2) and passing through another node n.
From these topological measures and centrality parameters, we can identify the co-patent network's global structure and infer the role of firms in the nanotechnology knowledge transfer model.
Findings and discussion
1 Small-medium firms do not operate as intermediaries between science and industry in nanotechnologies
The nanotechnology co-patent institution network is shown in Figure 1 and the main
topological parameters in Table 1. Nodes represent categories of institution: universities,
nonprofit institutions, governmental institutions, hospitals and firms. Links represent the co-
patent relations between different actors (analytical units), with line widths reflecting the
strength of the links between two nodes.
14
Figure 1 Institutional co-patenting network
Table 1 Topological measures of the institutional co-patenting network
The topological measures of the network (Table 1) show that the institutional co-patenting network only contains one connected component. At least one path exists between every pair of nodes in the institution‟s co-patenting network - in other words, every type of actor directly or indirectly affects actors of other types through nanotechnology co-patenting activities.
Based on the analysis of this network, we observe that:
- Firms in the large-very large category appear to co-patent mainly with universities and nonprofit institutions and to a lesser extent with SMEs and governments.
- The SME category co-patents with all other actors, but most closely with LVL firms.
Thus, Proposition 1 is not supported: nanotech SMEs do not play a key role in bridging the
gap between public research institutes and large companies, and so cannot be considered as
the central initial economic actors in nanotech networks.
15 2 Large firms are central in the nanotechnology firm co-patenting network
Figure 2 visualizes the co-patenting network activity among our 3,719 firms. The network density is very low and there are 2,865 isolated nodes and, in activity terms, only 854 firms (23%) co-patent with other firms. The network‟s topological measures (Table 2) show that the network contains 3,001 connected components, and the average number of neighbors is less than 1.
Figure 2 Firm’s co-patent network
Table 2 Topological measures of the firm’s co-patenting network
To gain finer-grained information, we focused our analysis on the core of the network (Figure
3), which yielded a testbed of 533 firms, 1,315 co-patent relations, and 533 self-patent
relations. The topological measures of the main firm co-patenting network (Table 3) shows
that at least one path exists between every pair of nodes – in other word every firm in this core
area of the network directly or indirectly affects another through co-patenting in
nanotechnology R&D.
16
Figure 3 Main firm’s co-patenting network colored by firm’s size
Table 3 Topological measures of the firm’s co-patenting core network
Analyzing this network, we can observe that large-very large firms are more closely related to
other firms, whereas small-medium firms are more peripheral, and this is confirmed by the
centrality parameters shown in Table 4. Based on firms with the top 40 highest eccentricity
indices, we can observe that only 8 of these (highlighted in the table) are SMEs, while the
other 32 firms are all large or very large firms. This implies that all firms in the co-patenting
network are in proximity with large-very large firms, suggesting that they play a more
17 important role in nanotechnology‟s knowledge transfer model than do small-medium firms.
These 32 large-very large firms have also high betweenness indices, suggesting they may act
as gatekeepers and/or connectors in nanotechnology networks. We can therefore say that
large-very large firms seem to play a central role in the process of co-production of
knowledge, so, in contrast with proposition 1, proposition 2 seems to be confirmed.
18
ID COMPANY_GEM COMPANY_Size_2L GeoArea_EN IncorporationYear_Q NAICS07_4D CentiScaPe Betweenness CentiScaPe Closeness CentiScaPe Eccentricity NanoIntensity_Q TotNbApp_Nano_Q TotNbApp_Q
JP0159 MITSUBISHI MATERIALS CORPORATION B.LVL Firms ASIA A.<=1950 Motor Vehicle Parts Manufacturing 61460.85476195142 5.589714924538849E-4 0.125 A.LOW(<10%) F.+500 F.+1000
US0129 APPLIED MATERIALS, INC. B.LVL Firms US & Canada B.1951-1980 Industrial Machinery Manufacturing 47949.06517827776 4.909180166912126E-4 0.125 B.MEDIUM(10-<50%) F.+500 F.+1000
TW0024 TAIWAN SEMICONDUCTOR MANUFACTURING CO LTD. (TSMC) B.LVL Firms ASIA C.1981-1990 Semiconductor and Other Electronic Component Manufacturing 2868.9806189453006 4.616805170821791E-4 0.125 A.LOW(<10%) F.+500 F.+1000
JP0321 TOKYO ELECTRON LIMITED B.LVL Firms ASIA B.1951-1980 Semiconductor and Other Electronic Component Manufacturing 19623.502016913702 5.277044854881266E-4 0.125 A.LOW(<10%) F.+500 F.+1000
JP0164 MITSUBISHI HEAVY INDUSTRIES, LTD. B.LVL Firms ASIA A.<=1950 Industrial Machinery Manufacturing 11084.916508366114 4.3010752688172043E-4 0.125 A.LOW(<10%) E.101-500 F.+1000
JP0056 FUJITSU LTD. B.LVL Firms ASIA A.<=1950 Computer and Peripheral Equipment Manufacturing 37456.9191659671 5.470459518599562E-4 0.125 A.LOW(<10%) F.+500 F.+1000
US6080 MULTIBEAM SYSTEMS INC A.SM Firms US & Canada D.>1990 Navigational, Measuring, Electromedical, and Control Instruments Manufacturing 3926.5015078040815 4.306632213608958E-4 0.125 B.MEDIUM(10-<50%) C.2-10 D.11-100
US0798 MICRON TECHNOLOGY, INC. B.LVL Firms US & Canada B.1951-1980 Semiconductor and Other Electronic Component Manufacturing 13523.706238206061 4.083299305839118E-4 0.125 A.LOW(<10%) F.+500 F.+1000
JP0255 SANYO ELECTRIC CO., LTD. B.LVL Firms ASIA A.<=1950 Communications Equipment Manufacturing 20235.109241973554 5.291005291005291E-4 0.1111111111111111 A.LOW(<10%) F.+500 F.+1000
JP0050 FUJI ELECTRIC CO., LTD. B.LVL Firms ASIA B.1951-1980 Electrical and Electronic Goods Merchant Wholesalers 1261.6108676325332 4.422821760283061E-4 0.1111111111111111 A.LOW(<10%) E.101-500 F.+1000
JP0549 INTERNATIONAL SUPERCONDUCTIVITY TECHNOLOGY CENTER B.LVL Firms ASIA C.1981-1990 Wired Telecommunications Carriers 14168.943449561868 5.305039787798408E-4 0.1111111111111111 B.MEDIUM(10-<50%) D.11-100 E.101-1000
US0848 MOTOROLA, INC. A.SM Firms US & Canada B.1951-1980 Electrical and Electronic Goods Merchant Wholesalers 22258.690783905502 4.0899795501022495E-4 0.1111111111111111 A.LOW(<10%) F.+500 F.+1000
FI0036 LEIRAS OY B.LVL Firms EU27 D.>1990 Drugs and Druggists' Sundries Merchant Wholesalers 0.0 4.23908435777872E-4 0.1111111111111111 B.MEDIUM(10-<50%) E.101-500 E.101-1000
JP0227 OKI ELECTRIC INDUSTRY CO., LTD. B.LVL Firms ASIA A.<=1950 Communications Equipment Manufacturing 1887.0849641355508 4.791566842357451E-4 0.1111111111111111 A.LOW(<10%) E.101-500 F.+1000
JP0157 MITSUBISHI ELECTRIC CORP (MITSUBISHI DENKI KK) B.LVL Firms ASIA A.<=1950 Other Electrical Equipment and Component Manufacturing 11835.32343061502 5.141388174807198E-4 0.1111111111111111 A.LOW(<10%) F.+500 F.+1000
JP0389 ASMO CO., LTD. B.LVL Firms ASIA A.<=1950 Electrical Equipment Manufacturing 0.0 4.310344827586207E-4 0.1111111111111111 A.LOW(<10%) C.2-10 F.+1000
US0059 AIR PRODUCTS AND CHEMICALS, INC. B.LVL Firms US & Canada A.<=1950 Basic Chemical Manufacturing 2122.0 3.90015600624025E-4 0.1111111111111111 A.LOW(<10%) F.+500 F.+1000
JP0329 TORAY INDUSTRIES, INC. B.LVL Firms ASIA A.<=1950 Resin, Synthetic Rubber, and Artificial Synthetic Fibers and Filaments Manufacturing 9033.327973488458 4.4543429844097997E-4 0.1111111111111111 A.LOW(<10%) F.+500 F.+1000
CA0275 WESTAIM TECHNOLOGIES INC A.SM Firms US & Canada D.>1990 Building Equipment Contractors 0.0 3.355704697986577E-4 0.1111111111111111 B.MEDIUM(10-<50%) D.11-100 E.101-1000
JP0335 TOTO, LTD. B.LVL Firms ASIA A.<=1950 Clay Product and Refractory Manufacturing 8381.284370631316 4.464285714285714E-4 0.1111111111111111 A.LOW(<10%) E.101-500 F.+1000
JP0432 DAIDO STEEL COMPANY LIMITED B.LVL Firms ASIA A.<=1950 Steel Product Manufacturing from Purchased Steel 2878.674593460698 4.5662100456621003E-4 0.1111111111111111 A.LOW(<10%) D.11-100 F.+1000
JP1971 TOKYO ELECTRON TOHOKU LTD B.LVL Firms ASIA D.>1990 Industrial Machinery Manufacturing 0.0 4.3497172683775554E-4 0.1111111111111111 A.LOW(<10%) C.2-10 E.101-1000
JP0193 NIPPON TELEGRAPH AND TELEPHONE CORPORATION (NTT) B.LVL Firms ASIA B.1951-1980 Wired Telecommunications Carriers 4435.428858232026 5.01002004008016E-4 0.1111111111111111 A.LOW(<10%) E.101-500 F.+1000
KR0049 SAMSUNG SDI CO., LTD. B.LVL Firms ASIA B.1951-1980 Semiconductor and Other Electronic Component Manufacturing 28417.805777555775 4.7192071731949034E-4 0.1111111111111111 A.LOW(<10%) F.+500 F.+1000
JP1156 MITSUBISHI RAYON CO LTD B.LVL Firms ASIA A.<=1950 Resin, Synthetic Rubber, and Artificial Synthetic Fibers and Filaments Manufacturing 1213.1456709956715 3.541076487252125E-4 0.1111111111111111 A.LOW(<10%) E.101-500 F.+1000
FR0325 MOTOROLA INC B.LVL Firms EU27 B.1951-1980 Electrical and Electronic Goods Merchant Wholesalers 0.0 3.894080996884735E-4 0.1111111111111111 A.LOW(<10%) E.101-500 F.+1000
DE2037 MARTIN GMBH FUER UMWELT-UND ENERGIETECHNIK B.LVL Firms EU27 A.<=1950 Other Specialty Trade Contractors 0.0 3.5014005602240897E-4 0.1111111111111111 B.MEDIUM(10-<50%) D.11-100 E.101-1000
JP2125 HITACHI AUTOMOT ENG CO LTD A.SM Firms ASIA B.1951-1980 Business Support Services 2316.865296743607 4.426737494466578E-4 0.1111111111111111 A.LOW(<10%) C.2-10 F.+1000
JP0595 KAWASAKI STEEL CORPORATION B.LVL Firms ASIA A.<=1950 Iron and Steel Mills and Ferroalloy Manufacturing 13075.814784964406 5.117707267144319E-4 0.1111111111111111 A.LOW(<10%) F.+500 F.+1000
DE0255 SIEMENS AG B.LVL Firms EU27 A.<=1950 Navigational, Measuring, Electromedical, and Control Instruments Manufacturing 17833.8803517486 4.5475216007276033E-4 0.1111111111111111 A.LOW(<10%) F.+500 F.+1000
US5771 AMERICAN CAN CO A.SM Firms US & Canada D.>1990 Metal and Mineral (except Petroleum) Merchant Wholesalers 0.0 4.23908435777872E-4 0.1111111111111111 A.LOW(<10%) D.11-100 F.+1000
JP0655 MITSUBISHI MATERIALS SILICON CORPORATION A.SM Firms ASIA B.1951-1980 Semiconductor and Other Electronic Component Manufacturing 2441.943877044865 4.675081813931744E-4 0.1111111111111111 A.LOW(<10%) D.11-100 E.101-1000
JP1522 PENTAX CORP B.LVL Firms ASIA A.<=1950 Commercial and Service Industry Machinery Manufacturing 4421.268862599342 4.178854993731718E-4 0.1111111111111111 A.LOW(<10%) E.101-500 F.+1000
JP0281 SONY CORP. B.LVL Firms ASIA A.<=1950 Audio and Video Equipment Manufacturing 75709.05982401127 5.747126436781609E-4 0.1111111111111111 A.LOW(<10%) F.+500 F.+1000
KR0110 SAMSUNG ELECTRONICS CO., LTD. B.LVL Firms ASIA B.1951-1980 Semiconductor and Other Electronic Component Manufacturing 17175.683269715013 4.84027105517909E-4 0.1111111111111111 A.LOW(<10%) F.+500 F.+1000
US0383 DIAMONEX, INCORPORATED A.SM Firms US & Canada D.>1990 Miscellaneous Durable Goods Merchant Wholesalers 0.0 3.894080996884735E-4 0.1111111111111111 C.HIGH(50-<100%) D.11-100 D.11-100
DE2883 EVONIK ROEHM GMBH B.LVL Firms EU27 A.<=1950 Pharmaceutical and Medicine Manufacturing 3302.6865934065677 3.566333808844508E-4 0.1111111111111111 A.LOW(<10%) E.101-500 F.+1000
US0037 ADVANCED TECHNOLOGY MATERIALS, INC. A.SM Firms US & Canada D.>1990 Semiconductor and Other Electronic Component Manufacturing 3466.190024984806 3.8109756097560977E-4 0.1111111111111111 B.MEDIUM(10-<50%) F.+500 F.+1000
JP1071 YOKOHAMA RUBBER CO., LTD. B.LVL Firms ASIA A.<=1950 Miscellaneous Nondurable Goods Merchant Wholesalers 200.6293650793648 3.766478342749529E-4 0.1111111111111111 A.LOW(<10%) D.11-100 F.+1000
JP0053 FUJI XEROX CO., LTD. B.LVL Firms ASIA B.1951-1980 Computer and Peripheral Equipment Manufacturing 1062.0 3.50385423966363E-4 0.1111111111111111 A.LOW(<10%) E.101-500 F.+1000
Table 4 Centrality measures of the Firms’ co-patent core network–Top 40-
19
Conclusions
Our results show first that the model of technology transfer is very different from that of biotechnology. Contrary to what happened in the development of the biotech sector, small and medium nanotech firms play an important technology-bringing role, but do not play the key role as translator of new knowledge between public research and industry. We know that small firms provide specific equipment and research services to very large companies: indeed, working at the nanotech level requires specific equipment, simulation models, first generation materials, devices and software. The nanotech-value chain is supported by a set of tools including scanning probe microscopes, nanofabrication tools, and computer modeling systems. Following Rosenberg‟s (1992) argument that scientific instruments can enable technologies that fuel subsequent down-stream discoveries, specific equipment, simulation models and specialized software play a similar role in nanotechnology R&D, and these are elements that are typically developed and commercialized by small firms. Government investment in the biotech sector was mainly channeled through supporting the creation of start-ups: but while this was quite successful in boosting technology transfer and the commercialization of R&D in that context, public policies designed to support nanotechnologies needs to be designed differently.
Our results reveal, secondly, that nanotechnology is being developed within large firms, along
the same pattern seen in the early phases of microelectronics, since nanotech development
requires the kind of large and diversifies knowledge bases that exist in large firms. At the
current stage of nanotechnology evolution, the process of exploration and knowledge
translation are based mainly on collaboration patterns inherited from earlier forms of
industrial organization. In microelectronics, government was both the principal organizer and
a major source of funding of large-scale research project – and in the same way, over $3bn of
government money world-wide has been pumped into the development of nanotechnologies
during the last couple of years, even though they are still in the early stage of their
technological life cycles. However, they promise exciting long-term pay-offs to those
governments that do invest.
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